Quasi-optimal scheduling algorithm for area coverage in multi-functional sensor networks

  • Authors:
  • Miklós Molnár;Gyula Simon;László Gönczy

  • Affiliations:
  • Department of Computer Science, University Montpellier 2, IUT, LIRMM, 161 rue Ada, 34095 Montpellier, Cedex 5, France;Department of Computer Science, University of Pannonia, Egyetem u. 10., H-8200, Veszprém, Hungary;Department of Measurement and Information Systems, Budapest University of Technology and Economics, Magyar tudósok krt. 2., H-1117, Budapest, Hungary

  • Venue:
  • International Journal of Ad Hoc and Ubiquitous Computing
  • Year:
  • 2013

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Abstract

Wireless sensor networks WSNs are widely used to perform measurement and monitoring tasks in large sensing fields. Several applications require every point in the monitored area to be covered by at least k sensors k-coverage problem for measurement accuracy or robustness. In heterogeneous multi-functional sensor networks, p parallel observation tasks are performed with p types of sensors, each task having its own kii = 1, 2,..., p coverage requirement, assuming that multi-functional sensors are used which may have multiple measurement capabilities multi-k-coverage problem. In order to prolong the lifetime of the network, active and sleeping states of sensors can be altered while maintaining the required coverage for all sensing tasks. In this paper an efficient distributed sensor state scheduling algorithm for multi-functional WSNs is proposed to solve the multi-k-coverage problem. The proposed multi-functional controlled greedy sleep algorithm is the generalisation of a recently proposed quasi-optimal scheduling algorithm. It is easy to implement and solves the common scheduling problem of heterogeneous multi-functional sensor networks. It has low local communication overhead and can adapt to dynamic changes in the network, while the required network-wide coverage for all sensing tasks is guaranteed as long as it is physically possible. The performance and the fault tolerance of the algorithm are illustrated by simulation examples.